ACMA中的联合对角化及其在多标签RFID系统中的应用

Padmapriya Duraisamy, Feng Zheng, T. Kaiser
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引用次数: 0

摘要

讨论了多标签射频识别(RFID)系统中信号的分离问题。首先,给出了RFID系统在单标签和多标签环境下的模型。然后,介绍了一种用于盲源分离问题的解析常模算法(ACMA)。本文考虑了一种利用联合对角化的方法来替代传统的ACMA。最后,将这两种ACMAs应用于多标签RFID环境,并对系统的性能进行了研究。对4-QAM和16-QAM调制进行了仿真,仿真结果表明,与传统的ACMA相比,采用联合对角化的ACMA所需的CPU时间更少,但平均模量误差(AME)更高。研究了系统性能随测量次数、信噪比、标签数量和阅读器天线数量的变化规律。在此基础上,提出了一些设计准则。有趣的是,这两种ACMA算法都适用于16-QAM情况,并且产量趋势与8-PSK和4-QAM相似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Joint diagonalization in ACMA and its application to multiple-tag RFID systems
This paper discusses the separation of signals in multiple-tag radio frequency identification (RFID) systems. First, a model for the RFID system in both single and multiple tag environments is presented. Then, an analytical constant modulus algorithm (ACMA) for the blind source separation problem is reviewed. An alternative approach to the traditional ACMA using joint diagonalization is considered. Finally, both the ACMAs are applied to the multiple-tag RFID environment and performance of the system is studied. Simulations are carried out for 4-QAM and 16-QAM modulations at tag and analyses of the simulation results reveal that the ACMA with joint diagonalization takes lesser CPU time to execute compared to the traditional ACMA, but with higher average modulus error (AME). The variation of system performance with the number of measurements, SNR (signal to noise ratio), number of tags and number of antennas at the reader is also studied. Based on these, some design guidelines are presented. Interestingly both the ACMA algorithms work for the 16-QAM case and yield trends similar to those of 8-PSK and 4-QAM.
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